To overcome this problem, existing works proposed the use of model-based linear controllers in addition to an RL controller to improve the transient learning performance [1]}, [2]}. Also, literature [3]} proposed a method that combines RL and model predictive control (MPC) to tackle the safety and stability issues in the exploration phase. However, these studies assumed that some form of plant model is available, which is often unlikely to be the case in practical situations. This motivates us to further develop a model-free approach for assisting the learning process of RL.
